Harmonic minimum mean squared error filters for multichannel speech enhancement
Jensen, Jesper Rindom ; Christensen, Mads Groesboll and Jakobsson, Andreas LU
(2017)
42nd IEEE International Conference on Audio, Speech, and Signals Processing, ICASSP 2017
p.501-505
- Abstract
Many state-of-the-art multichannel speech enhancement methods rely on second-order statistics of the desired speech signal, the noise signal, or both. Estimation of those are difficult in practice, resulting in a practical performance that is typically much lower than their potential theoretical performance. We propose two multichannel enhancement techniques that instead rely on a model for voiced speech. That is, the proposed methods are driven by the signals' fundamental frequencies, which may be accurately estimated even in noisy scenarios. The first method is designed independently of the microphone array geometry and source position, whereas these are utilized in the second approach. Thereby, we can investigate when to exploit such... (More)
Many state-of-the-art multichannel speech enhancement methods rely on second-order statistics of the desired speech signal, the noise signal, or both. Estimation of those are difficult in practice, resulting in a practical performance that is typically much lower than their potential theoretical performance. We propose two multichannel enhancement techniques that instead rely on a model for voiced speech. That is, the proposed methods are driven by the signals' fundamental frequencies, which may be accurately estimated even in noisy scenarios. The first method is designed independently of the microphone array geometry and source position, whereas these are utilized in the second approach. Thereby, we can investigate when to exploit such information in the case of localization errors and violations of the spatial assumptions. Numerical results show that the proposed method is able to outperform competing methods in terms of both output SNRs and PESQ scores.
(Less)
- author
- Jensen, Jesper Rindom
; Christensen, Mads Groesboll
and Jakobsson, Andreas
LU
- organization
- publishing date
- 2017-06-16
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- multichannel speech enhancement, voiced speech, MMSE filtering, harmonic filters, DOA mismatch
- host publication
- 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
- article number
- 7952206
- pages
- 5 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 42nd IEEE International Conference on Audio, Speech, and Signals Processing, ICASSP 2017
- conference location
- New Orleans, United States
- conference dates
- 2017-03-05 - 2017-03-09
- external identifiers
-
- scopus:85023776452
- scopus:85023776452
- ISBN
- 9781509041176
- DOI
- 10.1109/ICASSP.2017.7952206
- language
- English
- LU publication?
- yes
- id
- a0558000-3137-45e0-bd8e-63630c3cf8b0
- date added to LUP
- 2017-02-14 10:32:22
- date last changed
- 2022-03-01 19:30:45
@inproceedings{a0558000-3137-45e0-bd8e-63630c3cf8b0,
abstract = {{<p>Many state-of-the-art multichannel speech enhancement methods rely on second-order statistics of the desired speech signal, the noise signal, or both. Estimation of those are difficult in practice, resulting in a practical performance that is typically much lower than their potential theoretical performance. We propose two multichannel enhancement techniques that instead rely on a model for voiced speech. That is, the proposed methods are driven by the signals' fundamental frequencies, which may be accurately estimated even in noisy scenarios. The first method is designed independently of the microphone array geometry and source position, whereas these are utilized in the second approach. Thereby, we can investigate when to exploit such information in the case of localization errors and violations of the spatial assumptions. Numerical results show that the proposed method is able to outperform competing methods in terms of both output SNRs and PESQ scores.</p>}},
author = {{Jensen, Jesper Rindom and Christensen, Mads Groesboll and Jakobsson, Andreas}},
booktitle = {{2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings}},
isbn = {{9781509041176}},
keywords = {{multichannel speech enhancement; voiced speech; MMSE filtering; harmonic filters; DOA mismatch}},
language = {{eng}},
month = {{06}},
pages = {{501--505}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Harmonic minimum mean squared error filters for multichannel speech enhancement}},
url = {{http://dx.doi.org/10.1109/ICASSP.2017.7952206}},
doi = {{10.1109/ICASSP.2017.7952206}},
year = {{2017}},
}